The invention generally relates to security systems and, more particularly, to access monitoring and control systems for such security systems.
Access monitoring and control systems form a key component of security systems employed for a variety of private and public sites. Typically, access monitoring and control systems employ physical devices such as sensors, biometric scanners and keypad entry devices to track activity of individuals and/or objects through entrances to sites. It is desirable to monitor activities using such access monitoring and control systems and to identify any unusual patterns of inactivity. Typically, if an access control system indicates a lack of activity from a particular entrance to a site, it is difficult to find if the physical device located at such entrance is damaged or if there is some abnormal behavior at that entrance.
Certain systems look at historical time periods to determine the reasons for indication of lack of activity. However, through such conventional systems this requires obtaining several weeks of historical activity data and creating a behavioral model based upon such data. Further, certain systems examine such historical activity data on a daily basis to reduce training time for the behavioral model. Unfortunately, such techniques require large amounts of training data and also require high processing time for comparing any new activity with the training data.
It is therefore desirable to provide a real-time, efficient, reliable, and cost-effective technique for obtaining activity data for access monitoring and control systems. It is also desirable to provide techniques to analyze such activity data to detect any abnormal behavior or any potential problems with the system.